From Computer Science Wiki
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| == HL STUDENTS == | | == HL STUDENTS == |
| # I will open our classroom for any discussion about the email I sent to everyone
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| # We will review our homework (Outline the use of genetic algorithms)
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| # We will learn a bit about [[Neural network modeling]]
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| | | # we will learn about [[Compare different ways in which neural networks can be used to recognize patterns]] |
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| ## Outline the [[Structure of neural networks]]: | |
| ### input layer, minimum two hidden layers and an output layer
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| ### When enough neurons in a combination of neurons in one layer get 'activated,' they cause a neuron in the next layer to 'activate.'<ref>Franek, one of our 2019 students</ref>
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| ###
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| # We will thoroughly learn about [[Genetic algorithms]]
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| == SL STUDENTS == | | == SL STUDENTS == |
Latest revision as of 21:47, 11 February 2019
 What are we going to learn today?[edit]
Hello World!
HL STUDENTS[edit]
- we will learn about Compare different ways in which neural networks can be used to recognize patterns
SL STUDENTS[edit]
- You must work on your IA. Please compare your IA to the rubric on your "criterion guidance sheets" (found on google classroom)
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 What is our home learning?[edit]
- Please see google classroom
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 How am I being assessed today?[edit]
I will assess you formatively today, and make a professional judgement to what extent you understand our learning material. I will use observation, your written work, answers to questions, and contribution to class discussions as data to make my decisions.
I will also ask you to complete a self-assessment which I will use to help me gauge how well you think you understand our material in class.
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 As a computer scientist, you have:[edit]
- Confidence in dealing with complexity
- Persistence in working with difficult problems
- Tolerance for ambiguity
- The ability to deal with open-ended problems
- The ability to communicate and work with others to achieve a common goal or solution
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 Credits[edit]
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